Zhiting Zhu
Senior System Software Engineer at NVIDIA
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolZhiting Zhu is a Senior System Software Engineer based in Austin with 11 years of experience building and hardening high-performance systems in C++ and Rust. Currently at NVIDIA and Lepton AI, Zhiting blends deep distributed-systems research (PhD work on data processing and exactly-once semantics) with pragmatic engineering chops gained from internships at Google and Mozilla. He contributes to prominent open-source projects like rust-bindgen—implementing derive Eq support and improving edge-case handling—and has fixed build and reliability issues in industrial RAFT implementations used at scale. Comfortable across OS, compiler toolchains, and consensus systems, he has a track record of turning research into robust, production-ready fixes. Notably, his work spans both low-level kernel and runtime optimizations as well as cross-node memory sharing experiments with CXL pods, revealing a rare combination of systems research and production debugging.
11 years of coding experience
10 years of employment as a software developer
BS Computer Engineering, BS Computer Engineering at University of WashingtonDoctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at The University of Texas at AustinGuangzhou Tieyi Middle School
English, Chinese, Chinese
Stackoverflow
1reputation
0reached
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Github Skills (10)
binding10
data-storage10
distributed-systems10
c-language10
raft10
rust10
cprogramming-language10
ffi10
codegen9
testing9
Programming languages (18)
Github contributions (5)
rust-lang/rust-bindgen
Aug 2017 - Oct 2017
Automatically generates Rust FFI bindings to C (and some C++) libraries.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:15 commits, 18 PRs, 40 comments in 2 months
Contributions summary:Zhiting primarily focused on enhancing the `rust-bindgen` project by addressing code quality and functionality issues. They fixed misleading comments and improved documentation within the codebase. Furthermore, the user implemented and tested the derive `Eq` trait, which involves creating more complex tests and addressing edge cases, particularly with complex number representations and opaque types. The changes also demonstrate a good understanding of Rust's derive macros and associated code generation.
codegenrust-ffirustrust-ffi-bindingsffi
baidu/braft
Feb 2019 - Feb 2019
An industrial-grade C++ implementation of RAFT consensus algorithm based on brpc, widely used inside Baidu to build highly-available distributed systems.
Role in this project:Back-end Developer
Back-end DeveloperContributions:10 PRs, 10 comments, 1 issue in 4 days
Contributions summary:Zhiting focused on fixing compile warnings and errors within the `braft` project. Their contributions primarily involved correcting string literal issues, addressing potential logging conflicts, and resolving missing `AtExitManager` errors in several example applications. The user demonstrated an understanding of C++ and the project's build environment by modifying code across multiple files, including core library components and example programs. The fixes improved code quality and addressed potential compilation problems.
raft-consensusraft-consensus-algorithmdistributed-storageconsensusraft-protocol
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